TY - Generic
T1 - Modeling Study on Flexible Load’s Demand Response Potentials for Providing Ancillary Services at the Substation Level
Y1 - 2016/06//
A1 - Ryan Tulabing
A1 - Rongxin Yin
A1 - Nicholas DeForest
A1 - Yaping Li
A1 - Ke Wang
A1 - Taiyou Yong
A1 - Michael Stadler
KW - demand response
KW - Regression models
KW - simplifed DR potential estimation
KW - Thermostatically controlled loads
KW - two-state model
PB - Electric Power Systems Research
U2 - LBNL - 1005801
ER -
TY - JOUR
T1 - Modeling of Thermal Storage Systems in MILP Distributed Energy Resource Models
JF - Applied Energy
Y1 - 2015/01//
SP - 782
EP - 792
A1 - David Steen
A1 - Michael Stadler
A1 - Gonçalo Cardoso
A1 - Markus Groissböck
A1 - Nicholas DeForest
A1 - Chris Marnay
KW - distributed energy resources (der)
KW - Energy optimization
KW - Investment planning
KW - Renewables
KW - Thermal energy storage
AB - Thermal energy storage (TES) and distributed generation technologies, such as combined heat and power (CHP) or photovoltaics (PV), can be used to reduce energy costs and decrease CO2 emissions from buildings by shifting energy consumption to times with less emissions and/or lower energy prices. To determine the feasibility of investing in TES in combination with other distributed energy resources (DER), mixed integer linear programming (MILP) can be used. Such a MILP model is the well-established Distributed Energy Resources Customer Adoption Model (DER-CAM); however, it currently uses only a simplified TES model to guarantee linearity and short run-times. Loss calculations are based only on the energy contained in the storage. This paper presents a new DER-CAM TES model that allows improved tracking of losses based on ambient and storage temperatures, and compares results with the previous version. A multi-layer TES model is introduced that retains linearity and avoids creating an endogenous optimization problem. The improved model increases the accuracy of the estimated storage losses and enables use of heat pumps for low temperature storage charging. Results indicate that the previous model overestimates the attractiveness of TES investments for cases without possibility to invest in heat pumps and underestimates it for some locations when heat pumps are allowed. Despite a variation in optimal technology selection between the two models, the objective function value stays quite stable, illustrating the complexity of optimal DER sizing problems in buildings and microgrids.
PB - Elsevier
VL - 137
UR - http://www.sciencedirect.com/science/article/pii/S0306261914007181
U2 - LBNL-6757E
ER -
TY - JOUR
T1 - Microgrid Reliability Modeling and Battery Scheduling Using Stochastic Linear Programming
JF - Journal of Electric Power Systems Research
Y1 - 2013/06//
SP - 61
EP - 69
A1 - Gonçalo Cardoso
A1 - Michael Stadler
A1 - Afzal S. Siddiqui
A1 - Chris Marnay
A1 - Nicholas DeForest
A1 - Ana Barbosa-Póvoa
A1 - Paulo Ferrão
AB - This paper describes the introduction of stochastic linear programming into Operations DER-CAM, a tool used to obtain optimal operating schedules for a given microgrid under local economic and environmental conditions. This application follows previous work on optimal scheduling of a lithium-iron-phosphate battery given the output uncertainty of a 1 MW molten carbonate fuel cell. Both are in the Santa Rita Jail microgrid, located in Dublin, California. This fuel cell has proven unreliable, partially justifying the consideration of storage options. Several stochastic DER-CAM runs are executed to compare different scenarios to values obtained by a deterministic approach. Results indicate that using a stochastic approach provides a conservative yet more lucrative battery schedule. Lower expected energy bills result, given fuel cell outages, in potential savings exceeding 6%.
VL - 103
U2 - LBNL-6309E
ER -
TY - Generic
T1 - Microgrid Dispatch for Macrogrid Peak-Demand Mitigation
T2 - 2011 ACEEE Summer Study on Energy Efficiency in Buildings
Y1 - 2012/08//
A1 - Nicholas DeForest
A1 - Michael Stadler
A1 - Chris Marnay
A1 - Jonathan Donadee
JF - 2011 ACEEE Summer Study on Energy Efficiency in Buildings
CY - Pacific Grove, California
SN - 0-918249
U2 - LBNL-81939
ER -